Deep Neural Network Pretrained by Weighted Autoencoders and Transfer Learning for Retention Time Prediction of Small Molecules-Reference-Cited by-同舟云学术

Deep Neural Network Pretrained by Weighted Autoencoders and Transfer Learning for Retention Time Prediction of Small Molecules

Published:2021-11-15 Issue:47 Volume:93 Page:15651-15658
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Ju Ran¹,Liu Xinyu²^ORCID,Zheng Fujian²,Lu Xin²,Xu Guowang²^ORCID,Lin Xiaohui¹^ORCID

Affiliation:

1. School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China

2. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China

Funder

Ministry of Education of the People's Republic of China

Ministry of Science and Technology of the People's Republic of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.1c03250

Reference43 articles.

1. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites

2. Generalized Calibration Across Liquid Chromatography Setups for Generic Prediction of Small-Molecule Retention Times

3. Training, Selection, and Robust Calibration of Retention Time Models for Targeted Proteomics

4. Illuminating the dark matter in metabolomics

5. Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence

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